Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, P.O. Box 60 12 03, D-14412, Potsdam, Germany.
DLR Institute for Networked Energy Systems, Oldenburg, Germany.
Nat Commun. 2022 Aug 6;13(1):4593. doi: 10.1038/s41467-022-31942-9.
The dynamics of power consumption constitutes an essential building block for planning and operating sustainable energy systems. Whereas variations in the dynamics of renewable energy generation are reasonably well studied, a deeper understanding of the variations in consumption dynamics is still missing. Here, we analyse highly resolved residential electricity consumption data of Austrian, German and UK households and propose a generally applicable data-driven load model. Specifically, we disentangle the average demand profiles from the demand fluctuations based purely on time series data. We introduce a stochastic model to quantitatively capture the highly intermittent demand fluctuations. Thereby, we offer a better understanding of demand dynamics, in particular its fluctuations, and provide general tools for disentangling mean demand and fluctuations for any given system, going beyond the standard load profile (SLP). Our insights on the demand dynamics may support planning and operating future-compliant (micro) grids in maintaining supply-demand balance.
能耗动态是规划和运行可持续能源系统的重要组成部分。尽管可再生能源发电动态的变化已经得到了相当充分的研究，但对消费动态变化的理解仍有所欠缺。在这里，我们分析了奥地利、德国和英国家庭的高分辨率住宅用电数据，并提出了一种普遍适用的数据驱动的负载模型。具体来说，我们纯粹基于时间序列数据，从需求波动中分离出平均需求曲线。我们引入了一个随机模型来定量捕捉高度间歇的需求波动。由此，我们更好地理解了需求动态，特别是其波动，并为任何给定系统提供了一般的工具来分离平均需求和波动，超越了标准负荷曲线 (SLP)。我们对需求动态的洞察可以支持规划和运行符合未来要求的（微）电网，以维持供需平衡。
